(All_Primary cohort)
This pipeline computes the correlation between significantly recurrent gene mutations and selected clinical features.
Testing the association between mutation status of 15 genes and 7 clinical features across 23 patients, no significant finding detected with Q value < 0.25.
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No gene mutations related to clinical features.
Clinical Features |
Time to Death |
AGE |
PRIMARY SITE OF DISEASE |
GENDER |
LYMPH NODE METASTASIS |
TUMOR STAGECODE |
NEOPLASM DISEASESTAGE |
||
nMutated (%) | nWild-Type | logrank test | t-test | Fisher's exact test | Fisher's exact test | Chi-square test | t-test | Chi-square test | |
BRAF | 16 (70%) | 7 |
0.936 (1.00) |
0.447 (1.00) |
0.352 (1.00) |
0.626 (1.00) |
0.302 (1.00) |
0.681 (1.00) |
|
NRAS | 3 (13%) | 20 |
0.453 (1.00) |
1 (1.00) |
|||||
PRB2 | 4 (17%) | 19 |
0.368 (1.00) |
1 (1.00) |
0.557 (1.00) |
0.343 (1.00) |
0.156 (1.00) |
||
FAM135B | 6 (26%) | 17 |
0.45 (1.00) |
0.00415 (0.303) |
1 (1.00) |
0.621 (1.00) |
0.697 (1.00) |
0.469 (1.00) |
|
PTEN | 4 (17%) | 19 |
0.696 (1.00) |
0.125 (1.00) |
1 (1.00) |
0.343 (1.00) |
0.961 (1.00) |
||
TLL1 | 6 (26%) | 17 |
0.197 (1.00) |
0.0736 (1.00) |
1 (1.00) |
1 (1.00) |
0.302 (1.00) |
0.469 (1.00) |
|
ARID2 | 4 (17%) | 19 |
0.197 (1.00) |
0.37 (1.00) |
1 (1.00) |
0.273 (1.00) |
0.343 (1.00) |
0.961 (1.00) |
|
ZFHX4 | 8 (35%) | 15 |
0.936 (1.00) |
0.734 (1.00) |
0.779 (1.00) |
0.345 (1.00) |
0.404 (1.00) |
0.148 (1.00) |
|
CFHR1 | 5 (22%) | 18 |
0.782 (1.00) |
0.302 (1.00) |
1 (1.00) |
0.272 (1.00) |
0.959 (1.00) |
0.29 (1.00) |
|
OR52M1 | 3 (13%) | 20 |
0.319 (1.00) |
1 (1.00) |
1 (1.00) |
0.804 (1.00) |
0.339 (1.00) |
||
PPP6C | 3 (13%) | 20 |
0.453 (1.00) |
1 (1.00) |
|||||
RUNDC3B | 3 (13%) | 20 |
0.154 (1.00) |
0.453 (1.00) |
0.526 (1.00) |
0.191 (1.00) |
|||
ADCYAP1R1 | 3 (13%) | 20 |
0.0253 (1.00) |
0.224 (1.00) |
1 (1.00) |
1 (1.00) |
0.839 (1.00) |
0.928 (1.00) |
|
KCNC2 | 3 (13%) | 20 |
0.453 (1.00) |
0.209 (1.00) |
|||||
PIK3R1 | 4 (17%) | 19 |
0.332 (1.00) |
0.754 (1.00) |
1 (1.00) |
0.557 (1.00) |
0.0811 (1.00) |
0.505 (1.00) |
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Mutation data file = SKCM-All_Primary.mutsig.cluster.txt
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Clinical data file = SKCM-All_Primary.clin.merged.picked.txt
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Number of patients = 23
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Number of significantly mutated genes = 15
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Number of selected clinical features = 7
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Exclude genes that fewer than K tumors have mutations, K = 3
For survival clinical features, the Kaplan-Meier survival curves of tumors with and without gene mutations were plotted and the statistical significance P values were estimated by logrank test (Bland and Altman 2004) using the 'survdiff' function in R
For continuous numerical clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the clinical values between tumors with and without gene mutations using 't.test' function in R
For binary or multi-class clinical features (nominal or ordinal), two-tailed Fisher's exact tests (Fisher 1922) were used to estimate the P values using the 'fisher.test' function in R
For multi-class clinical features (nominal or ordinal), Chi-square tests (Greenwood and Nikulin 1996) were used to estimate the P values using the 'chisq.test' function in R
For multiple hypothesis correction, Q value is the False Discovery Rate (FDR) analogue of the P value (Benjamini and Hochberg 1995), defined as the minimum FDR at which the test may be called significant. We used the 'Benjamini and Hochberg' method of 'p.adjust' function in R to convert P values into Q values.
This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.